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Found 5 papers, 1 papers with code
Discrete Cosine Transform as Universal Sentence Encoder
Modern sentence encoders are used to generate dense vector representations that capture the underlying linguistic characteristics for a sequence of words, including phrases, sentences, or paragraphs.
Creating a Large Multi-Layered Representational Repository of Linguistic Code Switched Arabic Data
We present our effort to create a large Multi-Layered representational repository of Linguistic Code-Switched Arabic data.
Efficient Sentence Embedding using Discrete Cosine Transform
Vector averaging remains one of the most popular sentence embedding methods in spite of its obvious disregard for syntactic structure.
GW\_QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora
This paper describes our submission to SemEval-2017 Task 3 Subtask D, {``}Question Answer Ranking in Arabic Community Question Answering{''}.
Arabic Textual Entailment with Word Embeddings
Determining the textual entailment between texts is important in many NLP tasks, such as summarization, question answering, and information extraction and retrieval.
